低误码率LDPC解码器的设计与实现

Ashlesha P. Kshirsagar, Sandeep Kakde, M. Chawhan, Y. Suryawanshi
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引用次数: 1

摘要

许多高性能的低密度奇偶校验码都是基于由置换子矩阵组成的奇偶校验矩阵。仿真-仿真框架进一步允许迭代地重新定义算法和实现,以提高消息传递解码器的错误层性能。针对低密度奇偶校验码,提出了基于类对数罩比(LLR)的信念传播(BP)算法。描述了LLR-BP译码中校验节点更新计算的数值精确表示。介绍了低密度奇偶校验码(LDPC)解码器中和积算法(SPA)的实现,并利用校正项提高最小和算法(MSA)的译码性能。和积解码器中的量化和log-tanh函数近似对吸收集在误差底区占主导地位有很大影响。对于LDPC解码器,误码率随信噪比的增大而减小。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Design and Implementation of Low Bit Error Rate of LDPC Decoder
Many classes of high-performance Low-density parity check codes are based on parity check matrices composed of permutation sub matrices. The emulation-simulation framework further allows the algorithm and implementation to be iteratively redefined to improve the error floor performance of message passing decoder. Log-Like hood-Ratio (LLR) based Belief-Propagation (BP) algorithm is presented for Low Density Parity Check codes. Numerically accurate representation of check node update computation used in LLR-BP decoding is described. The implementation of Sum-Product algorithm (SPA) within Low Density Parity Check Code (LDPC) decoder is described in this paper and the correction term is used to improve the decoding performance of min-sum algorithm (MSA). Quantization and log-tanh function approximation in sum-product decoder strongly affect which absorbing set dominates in error floor region. For LDPC decoder, bit error rate (BER) decreases with increase in the signal to noise ratio.
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